摘要
信息融合应用中对冲突证据的有效处理一直是研究的热点,本文主要对多传感器信息融合过程中证据间的冲突进行了理论分析,并对开放世界里基于TBM模型的融合算法进行了研究,具体内容如下:
(1)对证据冲突产生的原因进行了深入分析,讨论了衡量冲突的表征因子,使用矛盾因子和赌博信度距离共同对冲突进行有效的定义和判断,引入了基于证据距离的证据一致性参数对证据进行修正,以保证融合的有效性并应用于故障诊断中。
(2)提出了针对数值属性获取一般信度指派值的方法。本方法首先构建了各个目标属性的三角模糊函数值和权重值,进而根据这些值获得目标属于各个类别的可能性,并通过归一化生成传感器报告的一般信度指派值。仿真结果证明该方法能够有效地应用于开放世界的信息融合。
(3)基于TBM模型提出了适用于开放世界的融合框架和决策方法。在表示层上对获取的信度值进行有效性判断及修正,降低了冲突信度对融合结果的影响,实现了冲突情况下信度的合成;在决策层上通过pignistic转换得到辨识框架中每个命题的概率分布,并采用基于规则的方法给出最终的识别结果。
The study of effective combination rules in DS theory when evidences are in conflict is always an interesting topic. This research is concentrated on analyzing the degree of conflict among evidences in Multi-Sensor Information Fusion System and proposing the combination rules based on the TBM model. The major works are as follows:
(1) Discussed what really constitutes a conflict among two beliefs, and proposed the new judgment of the conflict by using both the mass of the combined belief assigned to the empty set before normalization and the distance between betting commitments of beliefs. After analyzing the different fusion conditions defined by the two values, a set of rules guiding whether Dempster’s rule can be used or cannot be applied are proposed.
(2) Proposed the method of computing the general basic belief assignment used in the object detection in the open world. First, the triangle fuzzy number and the weight of all the properties are constructed based on the original data, then the general bbas of sensor reports which can be used in the information fusion of the open world are computed according to the triangle fuzzy numbers and their weights.
(3) Proposed the fusion model and the decision rules of the open world based on the TBM model. According to the belief assigned to the empty set of a bba and the value of the conflict among evidences, the general bbas obtained from sensor reports are abandoned or combined or updated on the fusion center of the credal level, and then translated into probability of each object by using the pignistic transformation when needed. The decisions are made using the pignistic probabilities derived from the bba by the pignistic transformation.
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